JamesGern/lorel.ai_long_train
TEXT GENERATIONConcurrency Cost:1Model Size:8BQuant:FP8Ctx Length:32kPublished:Apr 6, 2026License:apache-2.0Architecture:Transformer Open Weights Cold
JamesGern/lorel.ai_long_train is an 8 billion parameter Llama 3.1 instruction-tuned model developed by JamesGern. It was finetuned using Unsloth and Huggingface's TRL library, enabling 2x faster training. This model is optimized for general instruction-following tasks, leveraging the Llama 3.1 architecture for robust performance.
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Overview
JamesGern/lorel.ai_long_train is an 8 billion parameter instruction-tuned model based on the Llama 3.1 architecture. Developed by JamesGern, this model was finetuned using the Unsloth library and Huggingface's TRL library, which facilitated a 2x faster training process compared to standard methods.
Key Capabilities
- Instruction Following: Designed to accurately follow a wide range of user instructions.
- Efficient Training: Benefits from Unsloth's optimizations, allowing for quicker iteration and development.
- Llama 3.1 Foundation: Inherits the strong base capabilities of the Llama 3.1 model family.
Good For
- Developers looking for an efficiently trained Llama 3.1-based model.
- Applications requiring a capable 8B parameter model for instruction-tuned tasks.
- Experimentation with models finetuned using Unsloth's accelerated training techniques.